Image salient curve extraction is an important research direction in image processing field. Existing interactive methods for extracting image salient curve mainly include dynamic snakes method, intelligent scissors method, etc.
The dynamic snakes method is an important edge-based interactive method for extracting image salient curve. After the Snake model was first propounded by Kass, et al in 1987, the energy functions of and solving methods for this model have been being continuously improved and many new Snake models and improvements have been propounded. The basic idea of the dynamic snakes method is very simple. It matches template, which is spline curve generated by a plurality of control points, with local features of the image through elastic deformation of the template itself to achieve harmony, i.e., to achieve some kinds of minimization of energy function, to achieve the extraction of the image salient curve. However, the dynamic snakes method has some drawbacks: the location of initial curve is strictly limited, which must be very close to the real outline of the target, otherwise a bad convergence result will be obtained; good convergence effect cannot be obtained for concave outline of target; and speed of iteration is slow and convergence effect is not good.
The intelligent scissors method is a very classic semi-automatic method for extracting image salient curve. When a user moves the mouse approximately along an edge in an image, the intelligent scissors method can estimate a relatively accurate edge curve. The intelligent scissors method assigns weights to pixels by using Laplacian zero-crossing function, gradient magnitude and gradient directions, and solve a target contour between two points by way of solving an optimal path by dynamic programming. With the movement of the mouse, the intelligent scissors method can relatively accurately and quickly extract the contour of the target. When the mouse is moved to the vicinity of the contour of the target, the intelligent scissor can be automatically snapped onto the contour of the target. The intelligent scissors method also has some drawbacks: wrong input of the user cannot be identified, and the obtained curves are not smooth enough.